COOKIE: A Dataset for Conversational Recommendation over Knowledge Graphs in E-commerce
This provides a resource for researchers in conversational AI and e-commerce, but it is incremental as it focuses on dataset creation rather than novel methods.
The authors tackled the lack of datasets for conversational recommendation in e-commerce by creating COOKIE, a dataset built from Amazon reviews that integrates user-agent dialogues and knowledge graphs, enabling new research opportunities as demonstrated through baseline experiments.
In this work, we present a new dataset for conversational recommendation over knowledge graphs in e-commerce platforms called COOKIE. The dataset is constructed from an Amazon review corpus by integrating both user-agent dialogue and custom knowledge graphs for recommendation. Specifically, we first construct a unified knowledge graph and extract key entities between user--product pairs, which serve as the skeleton of a conversation. Then we simulate conversations mirroring the human coarse-to-fine process of choosing preferred items. The proposed baselines and experiments demonstrate that our dataset is able to provide innovative opportunities for conversational recommendation.